: We introduce the novel concept of graph alignment, a generalization of graph isomorphism that is motivated by the commonly used multiple sequence alignments. Graph alignments and...
Most current network intrusion detection systems employ signature-based methods or data mining-based methods which rely on labelled training data. This training data is typically ...
Graph data represents relationships, connections, or affinities. Innocent relationships produce repeated, and so common, substructures in graph data. We present techniques for dis...
Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...
Graph-based methods have gained attention in many areas of Natural Language Processing (NLP) including Word Sense Disambiguation (WSD), text summarization, keyword extraction and ...